Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
Insight
Executive Update
Data Integration Compliance
The purpose of this Executive Update is to discuss the conundrum of data integration and compliance as well as the roles that IT must play when addressing compliance issues.
Executive Update
Metadata: "Watch Out for That Tree!"
INTRODUCTION
It has been said that information is merely the correlation and selection of data and that, by extension, knowledge is the correlation and selection of information. I have said it myself. I was wrong.
Opening Statement
by Karl Wiig
Knowledge Management: People, Process, Technology
by Lynette Marling
A Behavioral Approach to Knowledge Management
by William Seidman and Michael McCauley
by Karl Wiig
Knowledge Management: People, Process, Technology
by Lynette Marling
A Behavioral Approach to Knowledge Management
by William Seidman and Michael McCauley
Opening Statement
by Karl Wiig
Knowledge Management: People, Process, Technology
by Lynette Marling
A Behavioral Approach to Knowledge Management
by William Seidman and Michael McCauley
by Karl Wiig
Knowledge Management: People, Process, Technology
by Lynette Marling
A Behavioral Approach to Knowledge Management
by William Seidman and Michael McCauley
Most companies recognize some flavor of the IT project lifecycle and use processes to manage each stage of the lifecycle. The common stages include project definition (including building the business case); project approval and prioritization; project development and implementation; ongoing operation, support, and maintenance; and finally, retirement.
Collaborations among knowledge workers are becoming increasingly important as organizations drive for globalization and innovation to achieve a competitive advantage. Meanwhile, work has become more and more knowledge-based, constantly requiring decisions to be made that are based on instant access to data from a diversity of information sources. This situation is especially common in the financial services industry.
To say that data quality is a huge problem is a gigantic understatement. Year after year, our surveys indicate that it continues to be the overwhelming concern among organizations developing data warehousing, BI, customer relationship management (CRM), business performance management, and a host of other information-intensive applications.